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isoSeQL: comparing long-read isoforms across multiple datasets.

Christine S Liu1,2, Jerold Chun1

  • 1Center for Neurologic Diseases, Sanford Burnham Prebys Medical Discovery Institute, La Jolla, CA 92037, United States.

Bioinformatics (Oxford, England)
|December 26, 2025
PubMed
Summary
This summary is machine-generated.

isoSeQL facilitates the comparison of RNA isoform profiles across multiple samples using long-read sequencing data. This tool aids in identifying common and unique isoforms and visualizing key metrics for transcriptomic analysis.

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Area of Science:

  • Genomics
  • Bioinformatics
  • Molecular Biology

Background:

  • Long-read sequencing advances RNA isoform detection and characterization.
  • Comparing RNA isoform profiles across multiple samples remains a significant challenge in transcriptomics.

Purpose of the Study:

  • To develop a bioinformatics tool, isoSeQL, for compiling and comparing long-read transcriptomic data across multiple samples.

Main Methods:

  • isoSeQL compiles long-read transcriptomic data.
  • It identifies common and unique RNA isoforms across samples.
  • The tool extracts and visualizes various transcriptomic metrics.

Main Results:

  • isoSeQL enables the identification of common and unique isoforms.
  • It facilitates the visualization of transcriptomic metrics for comparative analysis.
  • The tool's utility is demonstrated using publicly available datasets.

Conclusions:

  • isoSeQL enhances approaches utilizing long-read sequencing for isoform discovery and variation analysis.
  • It supports the examination of isoform differences across diverse experimental conditions and cell types.